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Accounting & Finance FinTech and Financial Analytics

Certificate for Module (Business Analytics and Web Scraping)
證書(單元 : 商業分析及網站擷取)

CEF Reimbursable Course

CEF Reimbursable Course

Course Code
FN057A
Application Code
2375-FN057A

Credit
6
Study mode
Part-time
Start Date
14 Mar 2026 (Sat)
Next intake(s)
Jun 2026
Duration
1 month to 2 months
Language
English
Course Fee
Course Fee: $10,100 per programme (* course fees are subject to change without prior notice)
Deadline on 27 Feb 2026 (Fri)
Enquiries
2867 8331 / 2867 8424
2861 0278
Apply Now

Today and Upcoming Events

10
Dec 2025
(Wed)

How to Design a Strong-Stock Analytics Dashboard System (强勢股分析系統)? (10 Dec 2025)

To design a stock price analytics system, we need to do the following: Collect historical stock prices Transform the collected stock price record to an appropriate format for presentation Present the transformed stock price datasets in a useful layout to facilitate analytics and investors’ review.   In this talk (webinar), the speaker will showcase how to design a Strong Stock Analytics Dashboard with a BI approach. This would give you a fresh view of the practical use of data automation and data visualization techniques.   During this webinar, you will explore how a Strong Stock Analytics Dashboard will help you to: review the recent trend of HSI identify the strong stocks and weak stocks based on a specified definition of price momentum compare the ratio between the strong stocks and weak stocks according to your selected price momentum definition do sectoral analysis of the strong / weak stocks   This is an advanced application of data analytics techniques with common financial data.  You will find this webinar inspiring and will give you food for thought on how to make use of learnt data techniques for financial stock investment analysis.   Sample Screenshots below:   Related Programme Links: Certificate for Module (Technical Analysis and Data Analytics for Stock Investment) - HKU SPACE: FinTech and Financial Intelligence, Data Science courses https://hkuspace.hku.hk/prog/exe-cert-in-interpretation-and-visualization-of-business-big-data https://hkuspace.hku.hk/prog/cert-for-module-business-intelligence-and-data-automation

17
Dec 2025
(Wed)

Any correlation between Bitcoin, Ethereum and Gold? And now Stablecoin Explained (17 Dec 2025)

Bitcoin and Ethereum are the most dominant cryptocurrencies, both accumulative account for over 90% in term of market capitalization excluding stablecoin, out of more than two thousands currently in the market. They are both in a form of digital asset that trades via various DEX or centralizated regulated trading platforms. However there are quite many key differences among them though. Bitcoin (BTC) is designed as a monetary storage (some proclaim as alternative of Gold) and medium of transaction and as an alternative to fiat currency. Ethereum (ETH), otherwise, is intended for complex smart contracts or dApps which contribute and act as key infrastructure of the emerging Web3.0 future. In light of recent rapid further innovation (like staking protocol) and adoption, the price of BTC and ETH have been risen more than double in past 12 months and also exhibited a huge volatility. The speaker will give a brief introduction of above crypto with some attention drawn to the relationship and correlation among Bitcoin, Ethereum, Gold, XRP and S&P500 – as shown in below charts. The speaker will then also talk about the latest development and impacts of the recently passed GENIUS Act in U.S. and the Stablecoins Ordinance (Cap. 656) in HK. To say, Stablecoin per se. is NOT referring the price to be fixed or stable, it’s referring to link or collateralize by some tangible asse shifting from no intrinsic value issue. At 10 Oct 2025, one of most selloff in crypto, USDe has experienced flash crash to as low as 0.65 USDEUST, per shown below. Source: Bloomberg   Language: Cantonese (Supplemented with English)

Accept new applications for Mar 2026 intake! There are practical classes in the computer laboratory. Our seasoned lecturer will discuss Descriptive analytics and data visualization using Microsoft Power BI, Predictive analytics and data modeling, Prescriptive analytics and business decision optimization as well as Managerial dashboard and storytelling. Welcome to your online application!

Highlights

The programme aims to provide students with essential knowledge to perform business analytics by processing, analysing, interpreting and visualizing business data. It discusses data wrangling and web scraping methods such as extraction of data from webpages and analysis of collected data to enhance business decision making. Besides, practical business applications of web scraping from managerial perspectives will be covered.

Big Data

Programme Details

On completion of the programme, students should be able to
1. describe how to perform business analytics and data wrangling;
2. apply computational tools to extract raw data from web and transform them to valuable managerial information;
3. analyse data for core business functions, interpret and visualize the processed information for operational efficiency; and
4. discuss the applications of web scraping to enhance business decision making.

Application Code 2375-FN057A Apply Online Now
Apply Online Now

Days / Time
  • Saturday, 1:30pm - 6:30pm
Duration
  • 30 hours per programme
Venue
  • Kowloon East Campus
  • Kowloon West Campus
  • Hong Kong Island Campus

Modules

Course Content :

(1) Web Scraping and Data Analytics

  • Overview of web analytics, web scrapping and data analytics
  • Introduction to web scrapping tools:
    • Microsoft PowerQuery
    • Python
    • Beautiful Soup
    • Wayscript
  • Applications of web scraping and data analytics with sample cases
    • Get a daily weather email report/SMS message for your city
    • Web scraping of stock prices
    • Ecommerce price tracker (receive an email whenever a price drops)

(2) Business Analytics and Data Wrangling

  • Principles of business analytics and data wrangling
  • Introduction to data cleansing using computation tools
  • Transformation of raw data to business information with sample cases
    • Standardize and cleanse sales budget
    • Unpivot tabular report data for processing
    • Merge and aggregate daily sales files for budget comparison
    • Automate data processing with one-click to refresh all

(3) Applications of Business Analytics and Web Scraping

  • Descriptive analytics and data visualization using Microsoft Power BI
  • Predictive analytics and data modeling
  • Prescriptive analytics and business decision optimization
  • Managerial dashboard and storytelling
  • Practical applications of business analytics and web scraping for core business functions
    • Building actual/budgeted sales management dashboard with one-click for data refresh
    • Trend analysis, data growth trend, drill up/down with hierarchy and exception highlights
    • Auto-generation of charts with natural language
    • Integration of web scraping with application programming interface (API), data cleansing and chart building
    • Predicting stock market sentiment with AI

Assessment method: Two in-class exercise + Group Project Presentation

Upon successful completion of the programme, students who have passed the continuous assessment and final assessment with attendance no less than 70% will be awarded within the HKU system through HKU SPACE a Certificate for Module (Business Analytics and Web Scraping)

Teacher

(1) Mr W. C. Chan
Mr W. C. Chan, FRM, is very professional in teaching web scraping using big data and visualize business data for storytelling. He possesses rich experience in financial risk management, information technology and data science and has worked as an IT Manager for over a decade. Being a practitioner in information technology, he is currently a consultant and trainer at a Big Data Consultancy Services Company. He is strong in cloud-based solutions, big data technology, data mining and machine learning.
Mr Chan has delivered trainings in data science areas, covering R, machine learning, statistics, database programming, AWS cloud architecture and SAS programming for IT professionals and university graduates for over 2 years. He worked as the Head of BI Data Analytics and R&D Team in Li & Fung Group Company, GBG Asia (HK) Limited, IDS Group Ltd. & LF Asia and so on, devoting himself in IT development and project management.
Mr Chan has obtained a Bachelor of Science Degree in Mathematics from The Chinese University of Hong Kong as well as three Master Degrees, namely, Risk Management Science from The Chinese University of Hong Kong, Quantitative Analysis for Business from City University of Hong Kong and Industrial Logistics Systems from The Hong Kong Polytechnic University.

(2) Ms Rowena Lai
Ms Lai is a practitioner in business and data analytics as well as web analytics. With a Bachelor of Science (Major in Mathematics and Minor in Economics) from The Chinese University of Hong Kong, two Master of Science degrees in  International Shipping and Transport Logistics as well as Global Supply Chain Management both from The Hong Kong Polytechnic University. She has worked with different industries on business analytics area. Ms. Lai is currently working in a leading bank and has led various projects related to data analytics. With her extended working exposure, she would like to share her academic knowledge and practical experience in data science and analytics.

(3) Mr Clive Yip
Mr Yip is a practitioner in Data Analytics.  He has 10 years of experience in both Big 4 consulting firms and multinational companies.  He is currently working as a Senior Data Analytics Consultant in a leading insurance company, using Python, SQL and other Big Data technologies to analyse and monitor any non-compliance or fraudulent activities.  He has a Master’s degree in Information Technology from HKUST and a Bachelor’s degree from the University of Southern California.  Before entering the data analytics field, he worked as a financial auditor in Ernst and Young and is a Certified Public Accountant (CPA) in Hong Kong and Canada.

(4) Mr Ken Choi
Mr Choi has over ten years of practical working experience across start-ups, data software companies, retail banking, insurance companies, listed companies, and large multinational corporation firms in areas of AI, business intelligence, big data and machine learning. He works as a senior project data analyst in charge of business process automation and data projects powered by AI, Machine Learning and Deep Learning. Moreover, he would like to leverage the Web 3.0 technology interaction with FinTech. Furthermore,  he applies business analytics to predict the revenue growth of the corporation. He has been actively teaching and coaching in different institutes and schools over the decade. He is a professional in communicating abstract data concepts and theory to non-tech students efficiently and effectively. He holds a Bachelor (Hons) in Statistics and Operation Research from HKBU and a Master of Statistics and Risk Management from HKU. He is a certified FRM (Financial Risk Manager), Certified Statistical Business Analyst, Certified Predictive Modeler: Enterprise Miner, Certified Advanced Programmer, Certified Base Programmer, and Certified System Platform Administrator. All 5 Credentials were approved by SAS Institute.

(5) Mr William Kin
Mr William Kin is a seasoned Business Analytics, Data Science, Engineering, and Governance professional with over a decade of experience in driving data-driven decision-making and ensuring robust data governance across diverse industries. With expertise in data strategy, advanced analytics, and compliance frameworks, William has a proven ability to design and implement BI tools, machine learning platforms, and data quality standards that align with organizational goals. His experience spans roles at leading organizations in property development, financial services, supply chain, and logistics, where he has successfully led digital transformation initiatives, optimized data processes, and ensured compliance with global data regulations. Equipped with technical proficiency in tools like Power BI, Python, SQL, and cloud platforms, William is a strategic thinker and leader who transforms data into actionable insights, empowering businesses to achieve growth, innovation, and operational excellence. His multidisciplinary expertise makes him a valuable asset in bridging the gap between data science, engineering, and governance to deliver measurable business outcomes.

(9) Mr William Ma
Mr Ma is a practitioner in data-driven solutions for business operations and user analytics. He holds a Master of Science in Computer Science (Financial Computing Stream) with Distinction from the University of Hong Kong, specialising in algorithmic trading, financial analytics, deep learning, and big data management. He completed his Bachelor of Business Administration in Professional Accounting and Information Systems with First Class Honours from The Hong Kong University of Science and Technology. Before transitioning into the business analytics field, Mr. Ma served as a senior accountant at Ernst & Young and is a Certified Public Accountant (CPA) in Hong Kong.

Class Details

Timetable

Lecture Date Time
1 14 Mar 26 (Sat) 13:30-18:30
2 21 Mar 26 (Sat) 13:30-18:30
3 28 Mar 26 (Sat) 13:30-18:30
4 11 Apr 26 (Sat) 13:30-18:30
5 18 Apr 26 (Sat) 13:30-18:30
6 25 Apr 26 (Sat) 13:30-18:30
     

Remarks: Tentative timetable is subject to change, and course commencement is subject to sufficient enrollment numbers.

Fee

Application Fee

HK$150 (Non-refundable)

Course Fee
  • Course Fee: $10,100 per programme (* course fees are subject to change without prior notice)

Entry Requirements

Applicants should hold an Advanced Diploma, a Higher Diploma or an Associate Degree preferably in the areas of business and statistics (e.g., mathematics, statistics, computer science, IT, engineering, economics or finance) awarded by a recognized institution. Applicants with other equivalent qualifications will be considered on individual merit.

 

CEF

  • The CEF Institution Code of HKU SPACE is 100
CEF Courses
CERTIFICATE FOR MODULE (BUSINESS ANALYTICS AND WEB SCRAPING)
證書(單元: 商業分析及網站擷取)
COURSE CODE 33C131609 FEES $10,100 ENQUIRY 2867-8331
Continuing Education Fund Continuing Education Fund
This course has been included in the list of reimbursable courses under the Continuing Education Fund.

Certificate for Module (Business Analytics and Web Scraping)

  • This course is recognised under the Qualifications Framework (QF Level [5])

Apply

Online Application Apply Now

Application Form Download Application Form

Enrolment Method
Payment Method
1. Cash, EPS, WeChat Pay Or Alipay

Course fees can be paid by cash, EPS, WeChat Pay or Alipay at any HKU SPACE Enrolment Centres.

2. Cheque Or Bank draft

Course fees can also be paid by crossed cheque or bank draft made payable to “HKU SPACE”. Please specify the programme title(s) for application and applicant’s name. You may either:

  • bring the completed form(s), together with the appropriate course or application fees in the form of a cheque, and any required supporting documents to any of the HKU SPACE enrolment centres;
  • or mail the above documents to any of the HKU SPACE Enrolment Centres, specifying “Course Application” on the envelope. HKU SPACE will not be responsible for any loss of personal information and payment sent by mail.
3. VISA/Mastercard

Applicants may also pay the course fee by VISA or Mastercard, including the “HKU SPACE Mastercard”, at any HKU SPACE enrolment centres. Holders of the HKU SPACE Mastercard can enjoy a 10-month interest-free instalment period for courses with a tuition fee worth a minimum of HK$2,000; however, the course applicant must also be the cardholder himself/herself. For enquiries, please contact our staff at any enrolment centres.

4. Online Payment

Online application / enrolment is offered for most open admission courses (enrolled on first come, first served basis) and selected award-bearing programmes. Application fees and course fees of these programmes/courses can be settled by using "PPS by Internet" (not available via mobile phones), VISA or Mastercard. In addition to the aforesaid online payment channels, new and continuing students of award-bearing programmes with available online service, they may also pay their course fees by Online WeChat Pay, Online Alipay or Faster Payment System (FPS). Please refer to Enrolment Methods - Online Enrolment  for details.

Notes

  • If the programme/course is starting within five working days, application by post is not recommended to avoid any delays. Applicants are advised to enrol in person at HKU SPACE Enrolment Centres and avoid making cheque payment under this circumstance.

  • Fees paid are not refundable except under very exceptional circumstances (e.g. course cancellation due to insufficient enrolment), subject to the School’s discretion. In exceptional cases where a refund is approved, fees paid by cash, EPS, WeChat Pay, Alipay, cheque, FPS or PPS by Internet will be reimbursed by a cheque, and fees paid by credit card will be reimbursed to the credit card account used for payment. 

  • In addition to the published fees, there may be additional costs associated with individual programmes. Please refer to the relevant course brochures or direct any enquiries to the relevant programme team for details.
  • Fees and places on courses cannot be transferrable from one applicant to another. Once accepted onto a course, the student may not change to another course without approval from HKU SPACE. A processing fee of HK$120 will be levied on each approved transfer.
  • HKU SPACE will not be responsible for any loss of payment, receipt, or personal information sent by mail.
  • For payment certification, please submit a completed form, a sufficiently stamped and self-addressed envelope, and a crossed cheque for HK$30 per copy made payable to “HKU SPACE” to any of our enrolment centres.